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Annually, businesses spend nearly $20 billion to $50 billion conducting leadership programmers, but a recent Accenture survey found that apart from eight percent management companies felt ineffective in developing leaders in their organization.
Failure in obtaining desired outcomes in leadership development is often the result of an organization inability to harness its leadership metrics. Machine learning, natural language processing, and big data analytics prove to be assets for leadership performance assessments.
Machine learning eliminates biased assessments from managers in an organization and helps them quickly identify top employees by leveraging data and analytics to compare employee performance.
Surveys provide a broader perspective on employee engagement and its challenges, but engagement is an emotional state that cannot be measured quantitatively. However, analytics being more scientific in comparison to engagement survey provides active insights into cultural challenges in the organization and employee retention.
Additionally, Leadership Analytics can help improve employee engagement by identifying activities that attribute largely to employee performance, which adds to the success of individuals as well as the company as a whole.
With online training gaining steam in a diverse work ecosystem, virtual classrooms helps employees gain a convenient and flexible experience. Online training also allows companies to keep track of employees’ engagement by assessing their understanding of the material. Every employee interaction during training from the assessment of the material to discussion forum responses creates detailed data that employers can analyze and decide ways of intervention.
Leadership Analytics can also help companies learn which areas, on the whole, need greater emphasis, allowing them to redirect training budgets into the right space.